De los me gusta al cambio: evaluación del impacto del compromiso ciudadano en las plataformas de redes sociales de la Comisión Europea

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DOI:

https://doi.org/10.56754/0718-4867.2024.3510

Resumen

Introducción: El auge de las redes sociales ha cambiado la comunicación de instituciones públicas, aumentando el diálogo con ciudadanos y presentando retos como privacidad y desinformación. Objetivos: Estudiar cómo la resonancia emocional en comunicaciones de la Comisión Europea en redes sociales afecta la participación pública. Metodología: Análisis de datos de redes sociales de la Comisión (Feb 2019 - Abr 2023) usando Fanpagekarma, evaluando métricas de participación y sentimientos con R. Resultados: Diferentes tonos emocionales en plataformas impactan en la participación; emociones positivas y negativas correlacionan con mayor interacción. Discusión: La resonancia emocional aumenta la participación, variando según la plataforma, lo que indica la necesidad de estrategias de comunicación específicas. Conclusiones: La resonancia emocional y adaptación a normas de plataformas son clave en la participación pública. Comprender estas dinámicas mejora la comunicación entre la Comisión Europea y el público.

Palabras Clave

redes sociales , administración pública , emociones , compromiso social y militante.

Allen, K., & Van-Zyl, I. (2020). Digital vigilantism, social media and cyber criminality. Enact/European Union.

Aust, F., & Barth, M. (2021). papaja: Prepare reproducible APA journal articles with R Markdown. GITHUB. https://github.com/crsh/papaja

Bae, K-S. (2023). sasLM: ’SAS’ linear model. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=sasLM

Bankston, J. (2021). Migration and smuggling across virtual borders: A European Union case study of internet governance and immigration politics. In Korkmaz, E. E. (Ed.), Digital Identity, Virtual Borders and Social Media (Chapter 5, pp. 73–97). Edward Elgar Publishing.

Barth, M. (2022). tinylabels: Lightweight variable labels. CRAN.R-PROJECT.ORG. https://cran.r-project.org/package=tinylabels

Bates, D., Maechler, M., & Jagan, M. (2023). Matrix: Sparse and dense matrix classes and methods. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=Matrix

Behrendt, S. (2023). Lm.beta: Add standardized regression coefficients to linear-model-objects. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=lm.beta

Bene, M., Ceron, A., Fenoll, V., Haßler, J., Kruschinski, S., Larsson, A. O., Magin, M., Schlosser, K., & Wurst, A-K. (2022). Keep them engaged! Investigating the effects of self-centered social media communication style on user engagement in 12 European countries. Political Communication, 39(4), 429–453. https://doi.org/10.1080/10584609.2022.2042435

Boboc, A., Gire, F., & Rosanvallon, J. (2015). Digital Social Networks. Sociologies pratiques, 30(1), 19–32. https://doi.org/10.3917/sopr.030.0019

Capriotti, P., & Zeler, I. (2023). Analysing effective social media communication in higher education institutions. Humanities and Social Sciences Communications, 10(656), 1-13. https://doi.org/10.1057/s41599-023-02187-8

Dahlgren, P. (2012). Social Media and Counter-Democracy: The Contingences of Participation. In Tambouris, E., Macintosh, A., & Sæbø, Ø. (Eds.), Electronic Participation (pp. 1–12). Springer. https://doi.org/10.1007/978-3-642-33250-0_1

Davison, A. C., & Hinkley, D. V. (1997). Bootstrap methods and their applications. Cambridge University Press. http://statwww.epfl.ch/davison/BMA/

De-Wilde, P., Rasch, A., & Bossetta, M. (2022). Analyzing citizen engagement with European politics on social media. Politics and Governance, 10(1), 90–96. https://doi.org/10.17645/pag.v10i1.5233

Dolan, R., Conduit, J., Fahy, J., & Goodman, S. (2016). Social media engagement behavior: A uses and gratifications perspective. Journal of Strategic Marketing, 24(3-4), 261–277. https://doi.org/10.1080/0965254X.2015.1095222

Doncel-Martín, I., Catalan-Matamoros, D., & Elías, C. (2023). Corporate social responsibility and public diplomacy as formulas to reduce hate speech on social media in the fake news era. Corporate Communications: An International Journal, 28(2), 340–352. https://doi.org/10.1108/CCIJ-04-2022-0040

Dragseth, M. R. (2020). Building student engagement through social media. Journal of Political Science Education, 16(2), 243–256. https://doi.org/10.1080/15512169.2018.1550421

Feinerer, I., Hornik, K., & Meyer, D. (2008). Text mining infrastructure in r. Journal of Statistical Software, 25(5), 1–54. https://doi.org/10.18637/jss.v025.i05

Flew, T., & Iosifidis, P. (2020). Populism, globalisation and social media. International Communication Gazette, 82(1), 7–25. https://doi.org/10.1177/1748048519880721

Fuchs, C. (2015). Social media and the public sphere. In Fuchs, C., Culture and Economy in the Age of Social Media (pp. 315–372). Routledge.

Genz, A., & Bretz, F. (2009). Computation of multivariate normal and t probabilities. Springer-Verlag.

Gohel, D., & Skintzos, P. (2023). Flextable: Functions for tabular reporting. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=flextable

Grolemund, G., & Wickham, H. (2011). Dates and times made easy with lubridate. Journal of Statistical Software, 40(3), 1–25. https://www.jstatsoft.org/v40/i03/

Grömping, U. (2006). Relative importance for linear regression in r: The package relaimpo. Journal of Statistical Software, 17(1), 1–27. https://doi.org/10.18637/jss.v017.i01

Gross, J., & Ligges, U. (2015). Nortest: Tests for normality. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=nortest

Hancu-Budui, A., Zorio-Grima, A., & Blanco-Vega, J. (2020). Audit institutions in the European Union: Public service promotion, environmental engagement and Covid crisis communication through social media. Sustainability, 12(23), 1-32. https://doi.org/10.3390/su12239816

Heath, R. L. (2018). How fully functioning is communication engagement if society does not benefit? In Johnston, K. A., & Taylor, M. (Eds.), The Handbook of Communication Engagement (1st ed., pp. 33-47). Wiley. https://doi.org/10.1002/9781119167600

Heldman, A. B., Schindelar, J., & Weaver, J. B. (2013). Social media engagement and public health communication: Implications for public health organizations being truly “social”. Public Health Reviews, 35(13), 1–18. https://doi.org/10.1007/BF03391698

Hornik, K. (2020). NLP: Natural language processing infrastructure. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=NLP

Kanol, D., & Nat, M. (2021). Group type and social media engagement strategies in the EU: The case of British interest groups on Facebook. Journal of Public and Nonprofit Affairs, 7(2), 205–219. DOI:10.20899/jpna.7.2.1-15

Kassambara, A. (2023a). Ggpubr: ’ggplot2’ based publication ready plots. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=ggpubr

____ (2023b). Rstatix: Pipe-friendly framework for basic statistical tests. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=rstatix

Kowalik, K. (2021). Social media as a distribution of emotions, not participation. Polish exploratory study in the EU smart city communication context. Cities, 108, 1-12. https://doi.org/10.1016/j.cities.2020.102995

Krzyżanowski, M. (2020). Digital Diplomacy or Political Communication? Exploring Social Media in The EU Institutions from a Critical Discourse Perspective 1. In Bjola, C., & Zaiotti, R. (Eds.), Digital Diplomacy and International Organisations (pp. 52–73). Routledge.

Long, J. A. (2019). Interactions: Comprehensive, user-friendly toolkit for probing interactions. CRAN.R-PROJECT.ORG. https://cran.r-project.org/package=interactions

Lumley, T. (2004). Analysis of complex survey samples. Journal of Statistical Software, 9(1), 1–19. DOI: 10.18637/jss.v009.i08

____ (2019). Mitools: Tools for multiple imputation of missing data. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=mitools

Marquart, F., Goldberg, A. C., & de-Vreese, C. H. (2020). “This time I’m (not) voting”: A comprehensive overview of campaign factors influencing turnout at European Parliament elections. European Union Politics, 21(4), 680–705. https://doi.org/10.1177/1465116520943670

Mascherini, M., & Nivakoski, S. (2022). Social media use and vaccine hesitancy in the European Union. Vaccine, 40(14), 2215–2225. DOI: 10.1016/j.vaccine.2022.02.059

Max, K. (2008). Building predictive models in r using the caret package. Journal of Statistical Software, 28(5), 1–26. https://doi.org/10.18637/jss.v028.i05

Mirbagheri, S., & Najmi, M. (2019). Consumers’ engagement with social media activation campaigns: Construct conceptualization and scale development. Psychology & Marketing, 36(4), 376–394. https://doi.org/10.1002/mar.21185

Müller, M. (2022). Spreading the word? European Union agencies and social media attention. Government Information Quarterly, 39(2), https://doi.org/10.1016/j.giq.2022.101682

Ooms, J. (2023). Writexl: Export data frames to excel ’xlsx’ format. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=writexl

Özdemir, S. F., & Rauh, C. (2022). A Bird’s eye view: Supranational EU Actors on Twitter. Politics and Governance, 10(1), 133–145. https://doi.org/10.17645/pag.v10i1.4686

Proellochs, N., & Feuerriegel, S. (2021). SentimentAnalysis: Dictionary-based sentiment analysis. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=SentimentAnalysis

R Core Team (2023). R: A language and environment for statistical computing. R FOUNDATION FOR STATISTICAL COMPUTING. https://www.R-project.org/

Revelle, W. (2023). Psych: Procedures for psychological, psychometric, and personality research. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=psych

Rus, M., Tasente, T., & Camara, V. (2021). Social media communication of public institutions. Case study: Representation of the European Commission in Romania. Technium Social Sciences Journal, 17(1), 119–135. https://techniumscience.com/index.php/socialsciences/article/view/2868

Sarkar, D. (2008). Lattice: Multivariate data visualization with r. Springer.

Smith, B. G., & Gallicano, T. D. (2015). Terms of engagement: Analyzing public engagement with organizations through social media. Computers in Human Behavior, 53, 82–90. https://doi.org/10.1016/j.chb.2015.05.060

Tasențe, T. (2014). Comunicarea politică prin social media și reacțiile publicului online. Editura Universitară.

____ (2023). Online communication of European public institutions and NATO during the crisis in Ukraine (February 24, 2022 - December 24, 2022). Technium Social Sciences Journal, 39(1), 195–206. https://doi.org/10.47577/tssj.v39i1.8187

Tasente, T., Carataș, M. A., & Alabdullah, T. T. Y. (2024). Analysis of sentiment in the European Central Bank’s social media activity during the Covid-19 pandemic and Ukraine War: A navigating crisis communication. Doxa Comunicación. Revista Interdisciplinar de Estudios de Comunicación y Ciencias Sociales, (38), 275-292. https://doi.org/10.31921/doxacom.n38a2051

Tasente, T., Rus, M., & Opariuc-Dan, C. (2023). Analysis of the online communication strategy of world political leaders during the War in Ukraine (February 24, 2022—January 23, 2023). Vivat Academia, (156), 246–270. https://doi.org/10.15178/va.2023.156.e1471

Tasente, T., Rus, M., & Tanase, G. (2024). From Outbreak to Recovery: An Observational Analysis of the Romanian Government’s Online Communication during and post-COVID-19. Vivat Academia, 157, 1–21. https://doi.org/10.15178/va.2024.157.e1513

Therneau, T., & Grambsch, P. (2000). Modeling survival data: Extending the Cox model. Springer.

Tierney, N., & Cook, D. (2023). Expanding tidy data principles to facilitate missing data exploration, visualization and assessment of imputations. Journal of Statistical Software, 105(7), 1–31. https://doi.org/10.18637/jss.v105.i07

Van-Dijck, J., & Poell, T. (2015). Social Media and the Transformation of Public Space. Social Media + Society, 1(2). https://doi.org/10.1177/2056305115622482

Venables, W. N., & Ripley, B. D. (2002). Modern applied statistics with s (Fourth Edition). Springer. https://www.stats.ox.ac.uk/pub/MASS4/

Voorveld, H. A., Van-Noort, G., Muntinga, D. G., & Bronner, F. (2018). Engagement with social media and social media advertising: The differentiating role of platform type. Journal of Advertising, 47(1), 38–54. https://doi.org/10.1080/00913367.2017.1405754

Wei, Y., Gong, P., Zhang, J., & Wang, L. (2021). Exploring public opinions on climate change policy in" Big Data Era" case study of the European Union Emission Trading System (EU-ETS) based on Twitter. Energy Policy, 158, 1-14. https://doi.org/10.1016/j.enpol.2021.112559

Wickham, H. (2016). ggplot2: Elegant graphics for data analysis. Springer-Verlag. https://ggplot2.tidyverse.org

Wickham, H., & Bryan, J. (2023). Readxl: Read excel files. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=readxl

Wickham, H., François, R., Henry, L., Müller, K., & Vaughan, D. (2023). Dplyr: A grammar of data manipulation. CRAN.R-PROJECT.ORG. https://CRAN.R-project.org/package=dplyr

Xie, Y. (2015). Dynamic documents with R and knitr (2nd ed.). Chapman and Hall/CRC.

Yanagida, T. (2023). Misty: Miscellaneous functions’t. yanagida’. CRAN.R-PROJECT.ORG. https://cran.r-project.org/package=misty

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Publicado

2024-03-18

Cómo citar

Tasențe, T., Sandu, M. L., & Popescu, C.-D. (2024). De los me gusta al cambio: evaluación del impacto del compromiso ciudadano en las plataformas de redes sociales de la Comisión Europea. Perspectivas De La Comunicación, 17. https://doi.org/10.56754/0718-4867.2024.3510

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Vol. 17 (2024): (Publicación continua)

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Derechos de autor 2024 Tănase Tasențe, Mihaela Luminița Sandu, Cristina-Dana Popescu

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